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SUMMARY:Training course: Data assimilation
DTSTART:20210510T074500Z
DTEND:20210514T160000Z
DTSTAMP:20260312T203900Z
UID:indico-event-208@events.ecmwf.int
CONTACT:events@ecmwf.int
DESCRIPTION:This course was a remote event.\n\nThis five-day module focuse
 s on describing data assimilation methods and general aspects of assimilat
 ing observations. Aspects of the implementation of the assimilation techni
 ques for real-size numerical weather prediction (NWP) systems will also be
  described.\n\nAs well as lectures there will be discussion and hands-on s
 essions.\n\nMain topics\n\n\n	The fundamental data assimilation concepts\n
 	Optimal Interpolation\, 3D-Var\, 4D-Var and the Kalman filter\n	Ensemble 
 Kalman Filter methods\; Ensemble of Data Assimilations and uncertainty est
 imation\; Hybrid variational/ensemble based methods\n	Modelling of error c
 ovariances\; handling of non-Gaussian errors\n	The global observing system
 \, with emphasis on how to use satellite observations\n	Bias correction\, 
 quality control and diagnostics\n	Applications of data assimilation method
 s for the land surface\, ocean\, atmospheric composition and reanalysis\n\
 n\nRequirements\n\nParticipants should have a good meteorological and math
 ematical background\, and in particular a good understanding of linear alg
 ebra. They are expected to be familiar with the contents of standard meteo
 rological and mathematical textbooks.\n\nIf you are less familiar with dat
 a assimilation concepts\, such as Bayes Theorem\, you may wish to consider
  attending the University of Reading Introductory course\, which runs the 
 week before our course\; see details below.\n\nIntroductory material not c
 overed by the course can be found in our lecture note series.\n\nSome prac
 tical experience in numerical weather prediction is an advantage.\n\nAll l
 ectures will be given in English.\n\nhttps://events.ecmwf.int/event/208/
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URL:https://events.ecmwf.int/event/208/
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